Evidence map›Paper›PMID 42215957›Full record

SynthesisBMC musculoskeletal disorders2026

Performance of prediction models for delayed union and nonunion after fracture: a systematic review and meta-analysis.

Fengsheng Yin, Xiangjin Wang, Gan Luo, Zhen Deng, Wentao Chen, Yu Zhang

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC musculoskeletal disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Fengsheng YinDepartment of Orthopedics, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, 610041, Sichuan, China.ORCID http://orcid.org/0009-0008-1350-7165
Xiangjin WangSchool of Clinical Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan, China.ORCID http://orcid.org/0009-0003-4101-6666
Gan LuoDepartment of Orthopedics, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, 610041, Sichuan, China.ORCID http://orcid.org/0000-0001-6570-8673
Zhen DengSchool of Acupuncture and Massage Therapy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China.ORCID http://orcid.org/0009-0000-7644-3738
Wentao ChenDepartment of Orthopedics, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, 610041, Sichuan, China.ORCID http://orcid.org/0009-0005-5619-657X
Yu ZhangDepartment of Orthopedics, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, 610041, Sichuan, China. 3804919972@qq.com.

Funding

Sichuan Provincial Administration of Traditional Chinese Medicine 25MSZX207
6 · The paper itself

Abstract

backgroundDelayed union and nonunion are common and costly complications after fractures, yet early risk stratification remains challenging. We systematically reviewed and meta-analyzed multivariable prediction models for compromised fracture healing.

methodsMEDLINE, EMBASE, CINAHL, SinoMed, and CNKI were searched from inception to 30 November 2025. Studies developing or validating models predicting delayed union, nonunion, or related healing outcomes after fractures were included. Risk of bias was assessed with PROBAST and certainty of evidence with GRADE. Discrimination was summarized using the area under the receiver operating characteristic curve (AUC), pooled with random-effects models by validation tier (apparent performance, internal validation, external validation), and further described by anatomical subgroup. The protocol was registered in PROSPERO (CRD420251252244).

resultsSeventy-seven studies reporting 97 model entries were included across appendicular, proximal femoral, multisite, and axial skeletal fracture settings; 56 models reported apparent performance only, 28 had internal validation, and 13 underwent external validation. Pooled AUC was 0.88 (95% CI 0.86-0.90) for apparent performance, 0.72 (95% CI 0.41-0.90) for internal validation, and 0.81 (95% CI 0.73-0.86) for external validation, with substantial heterogeneity. Apparent performance exceeded validated performance (mean optimism 0.052).

conclusionExisting models often show optimistic apparent discrimination; however, discrimination alone is insufficient to justify clinical implementation, especially given limited external validation, sparse calibration reporting, major clinical and anatomical heterogeneity, and high risk of bias. Future studies should prioritize clearer outcome definitions, robust methodology, transparent reporting, independent external validation with calibration assessment, and evaluation of clinical utility before these models are used to guide care.

Indexed as

Fracture HealingFractures, BoneFractures, UnunitedHumansPrediction AlgorithmsPredictive Learning ModelsRisk AssessmentDelayed unionFracture healingMeta-analysisNonunionPrediction modelSystematic review

Identifiers

PMID42215957
PMCPMC13242139

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.